1058 Courses in Cardiff delivered Online

Duration 1 Days 6 CPD hours This course is intended for System administrators and security operations personnel, including analysts and managers Overview By the end of the course, you should be able to meet the following objectives: Manage and configure the Carbon Black App Control sever based on organizational requirements. Implement rules to support business processes and automatic approvals. Identify scenarios and use cases for Custom rules and Event rules. Describe common troubleshooting scenarios for the Carbon Black App Control server. Describe common troubleshooting scenarios for the Carbon Black App Control Windows agent. This course teaches you how to configure and scope the rules within VMware Carbon Black© App ControlTM product to maintain the system according to your organization?s security posture and organizational policies. Additionally, this course covers troubleshooting both the server and the agent for Carbon Black App Control and how to identify issues that impact normal operations. This course provides an in-depth, technical understanding of the Carbon Black App Control product through comprehensive coursework and hands-on scenario-based labs. Course Introduction Introductions and course logistics Course objectives Custom Rules Basics Execute / Write action rules Precedence Paths tom Rules Best Practices Rule Triad Rule multiplication Rule Types Custom rule type overview Optimizing Custom Rules Evaluating events Event Rules Creating and editing Testing before implementing Creating and editing Testing before implementing Server versus agent issues Server Capabilities Tools, logs, common issues, scenarios Agent Capabilities Tools, logs, common issues, scenarios

Register on the Machine Learning Basics today and build the experience, skills and knowledge you need to enhance your professional development and work towards your dream job. Study this course through online learning and take the first steps towards a long-term career. The course consists of a number of easy to digest, in-depth modules, designed to provide you with a detailed, expert level of knowledge. Learn through a mixture of instructional video lessons and online study materials. Receive online tutor support as you study the course, to ensure you are supported every step of the way. Get a digital certificate as a proof of your course completion. The Machine Learning Basics is incredibly great value and allows you to study at your own pace. Access the course modules from any internet-enabled device, including computers, tablet, and smartphones. The course is designed to increase your employability and equip you with everything you need to be a success. Enrol on the now and start learning instantly! What You Get With The Machine Learning Basics Receive an e-certificate upon successful completion of the course Get taught by experienced, professional instructors Study at a time and pace that suits your learning style Get instant feedback on assessments 24/7 help and advice via email or live chat Get full tutor support on weekdays (Monday to Friday) Certificate of Achievement Endorsed Certificate of Achievement from the Quality Licence Scheme Upon successful completion of the final assessment, you will be eligible to apply for the Quality Licence Scheme Endorsed Certificate of achievement. This certificate will be delivered to your doorstep through the post for £119. An extra £10 postage charge will be required for students leaving overseas.  CPD Accredited Certificate After the successful completion of the final assessment, you will receive a CPD-accredited certificate of achievement. The PDF certificate is for 9.99, and it will be sent to you immediately after through e-mail. You can get the hard copy for 15.99, which will reach your doorsteps by post.  Who Is This Course For The course is ideal for those who already work in this sector or are an aspiring professional. This course is designed to enhance your expertise and boost your CV. Learn key skills and gain a professional qualification to prove your newly-acquired knowledge. Requirements The online training is open to all students and has no formal entry requirements. To study the Machine Learning Basics, all your need is a passion for learning, a good understanding of English, numeracy, and IT skills. You must also be over the age of 16. Course Content Section 01: Introduction Introduction to Supervised Machine Learning 00:06:00 Section 02: Regression Introduction to Regression 00:13:00 Evaluating Regression Models 00:11:00 Conditions for Using Regression Models in ML versus in Classical Statistics 00:21:00 Statistically Significant Predictors 00:09:00 Regression Models Including Categorical Predictors. Additive Effects 00:20:00 Regression Models Including Categorical Predictors. Interaction Effects 00:18:00 Section 03: Predictors Multicollinearity among Predictors and its Consequences 00:21:00 Prediction for New Observation. Confidence Interval and Prediction Interval 00:06:00 Model Building. What if the Regression Equation Contains 'Wrong' Predictors? 00:13:00 Section 04: Minitab Stepwise Regression and its Use for Finding the Optimal Model in Minitab 00:13:00 Regression with Minitab. Example. Auto-mpg: Part 1 00:17:00 Regression with Minitab. Example. Auto-mpg: Part 2 00:18:00 Section 05: Regression Trees The Basic idea of Regression Trees 00:18:00 Regression Trees with Minitab. Example. Bike Sharing: Part1 00:15:00 Regression Trees with Minitab. Example. Bike Sharing: Part 2 00:10:00 Section 06: Binary Logistics Regression Introduction to Binary Logistics Regression 00:23:00 Evaluating Binary Classification Models. Goodness of Fit Metrics. ROC Curve. AUC 00:20:00 Binary Logistic Regression with Minitab. Example. Heart Failure: Part 1 00:16:00 Binary Logistic Regression with Minitab. Example. Heart Failure: Part 2 00:18:00 Section 07: Classification Trees Introduction to Classification Trees 00:12:00 Node Splitting Methods 1. Splitting by Misclassification Rate 00:20:00 Node Splitting Methods 2. Splitting by Gini Impurity or Entropy 00:11:00 Predicted Class for a Node 00:06:00 The Goodness of the Model - 1. Model Misclassification Cost 00:11:00 The Goodness of the Model - 2 ROC. Gain. Lit Binary Classification 00:15:00 The Goodness of the Model - 3. ROC. Gain. Lit. Multinomial Classification 00:08:00 Predefined Prior Probabilities and Input Misclassification Costs 00:11:00 Building the Tree 00:08:00 Classification Trees with Minitab. Example. Maintenance of Machines: Part 1 00:17:00 Classification Trees with Miitab. Example. Maintenance of Machines: Part 2 00:10:00 Section 08: Data Cleaning Data Cleaning: Part 1 00:16:00 Data Cleaning: Part 2 00:17:00 Creating New Features 00:12:00 Section 09: Data Models Polynomial Regression Models for Quantitative Predictor Variables 00:20:00 Interactions Regression Models for Quantitative Predictor Variables 00:15:00 Qualitative and Quantitative Predictors: Interaction Models 00:28:00 Final Models for Duration and Total Charge: Without Validation 00:18:00 Underfitting or Overfitting: The 'Just Right Model' 00:18:00 The 'Just Right' Model for Duration 00:16:00 The 'Just Right' Model for Duration: A More Detailed Error Analysis 00:12:00 The 'Just Right' Model for Total Charge 00:14:00 The 'Just Right' Model for Toral Charge: A More Detailed Error Analysis@@ 00:06:00 Section 10: Learning Success Regression Trees for Duration and TotalCharge 00:18:00 Predicting Learning Success: The Problem Statement 00:07:00 Predicting Learning Success: Binary Logistic Regression Models 00:17:00 Predicting Learning Success: Classification Tree Models 00:09:00 Order your Certificates & Transcripts Order your Certificates & Transcripts 00:00:00 Frequently Asked Questions Are there any prerequisites for taking the course? There are no specific prerequisites for this course, nor are there any formal entry requirements. All you need is an internet connection, a good understanding of English and a passion for learning for this course. Can I access the course at any time, or is there a set schedule? You have the flexibility to access the course at any time that suits your schedule. Our courses are self-paced, allowing you to study at your own pace and convenience. How long will I have access to the course? For this course, you will have access to the course materials for 1 year only. This means you can review the content as often as you like within the year, even after you've completed the course. However, if you buy Lifetime Access for the course, you will be able to access the course for a lifetime. Is there a certificate of completion provided after completing the course? Yes, upon successfully completing the course, you will receive a certificate of completion. This certificate can be a valuable addition to your professional portfolio and can be shared on your various social networks. Can I switch courses or get a refund if I'm not satisfied with the course? We want you to have a positive learning experience. If you're not satisfied with the course, you can request a course transfer or refund within 14 days of the initial purchase. How do I track my progress in the course? Our platform provides tracking tools and progress indicators for each course. You can monitor your progress, completed lessons, and assessments through your learner dashboard for the course. What if I have technical issues or difficulties with the course? If you encounter technical issues or content-related difficulties with the course, our support team is available to assist you. You can reach out to them for prompt resolution.

The Warehouse Management is a wonderful learning opportunity for anyone who has a passion for this topic and is interested in enjoying a long career in the relevant industry. It's also for anyone who is already working in this field and looking to brush up their knowledge and boost their career with a recognised certification. This Warehouse Management consists of several modules that take around 6 hours to complete. The course is accompanied by instructional videos, helpful illustrations, how-to instructions and advice. The course is offered online at a very affordable price. That gives you the ability to study at your own pace in the comfort of your home. You can access the modules from anywhere and from any device. Why choose this course Earn an e-certificate upon successful completion. Accessible, informative modules taught by expert instructors Study in your own time, at your own pace, through your computer tablet or mobile device Benefit from instant feedback through mock exams and multiple-choice assessments Get 24/7 help or advice from our email and live chat teams Full Tutor Support on Weekdays Course Design The course is delivered through our online learning platform, accessible through any internet-connected device. There are no formal deadlines or teaching schedules, meaning you are free to study the course at your own pace. You are taught through a combination of Video lessons Online study materials Mock exams Multiple-choice assessment Certification Upon successful completion of the course, you will be able to obtain your course completion PDF Certificate at £9.99. Print copy by post is also available at an additional cost of £15.99 and the same for PDF and printed transcripts.

24-Hour Knowledge Knockdown! Prices Reduced Like Never Before Imagine turning your hustle into a thriving online business. The UK e-commerce market is on fire, projected to hit a cool £500 billion this year. But with so much competition, how do you stand out? This jam-packed Diploma in Ecommerce Products, Brands & Services equips you with the skills to dominate the digital marketplace. This course goes beyond just selling stuff online. It covers everything from product development, brand management to service delivery in an online environment. You will learn strategic marketing and social media tactics to grab customer attention. Master SEO to become a search engine magnet, and learn product photography that converts clicks into sales. Plus, hone your sales skills and decision-making chops to thrive in the fast-paced world of e-commerce. With a single payment, you will gain access to Ecommerce course, including 10 premium courses, a QLS Endorsed Hardcopy certificate (for the title course) and 11 PDF certificates for Absolutely free. This Ecommerce Bundle Package includes: Course 01: Diploma in E-Commerce Management at QLS Level 5 10 Additional CPDQS Accredited Premium Courses - Course 01: Strategic Marketing & Planning Course 02: Social Media Marketing Strategy Course 03: SEO and Digital Marketing Diploma Course 04: Facebook Marketing Strategy Course 05: Sales Skills Course Course 06: Creative Writing Skills Course 07: Product Photography Course 08: YouTube Marketing Strategy Course 09: Transport and Logistics Management Course 10: Decision-Making in High-Stress Situations Success becomes a lot simpler with this bundle package, which allows you to monetise your skills. This bundle is appropriate for both part-time and full-time students, and it can be completed at your own pace. Learning Outcomes of Ecommerce Products, Brands, and Services Understand the fundamentals of ecommerce and the theories behind it. Gain insights into the development and management of ecommerce products. Learn the principles of creating and managing brands in an online environment. Explore the dynamics of service delivery in ecommerce. Understand customer behaviours and expectations in digital commerce. Learn how to create engaging online shopping experiences. Gain knowledge on the role of digital marketing in promoting ecommerce products, brands, and services. Why Choose Us? Get a Free QLS Endorsed Certificate upon completion of Ecommerce Get a free student ID card with Ecommerce Training program (£10 postal charge will be applicable for international delivery) The Ecommerce is affordable and simple to understand This course is entirely online, interactive lesson with voiceover audio Get Lifetime access to the Ecommerce course materials The Ecommerce comes with 24/7 tutor support After Completing this Ecommerce Products, Brands, and Services course, you can progress towards- COB Certified E-Commerce Manager Level 5 Diploma in IT - E-commerce and much more... Start your learning journey straight away with this bundle and take a step toward a brighter future! *** Course Curriculum: *** The bundle courses have the following curriculum: Course 01: Diploma in E-Commerce Management at QLS Level 5 Module 1: Introduction to Electronic Commerce Module 2: Ecommerce Strategy and Implementation Module 3: Customer Service Module 4: Products, Brands, and Services Module 5: Content Planning and Production Module 6: Use of Social Networks Module 7: Marketing Module 8: Creating an Engaging User Experience Module 9: Transaction Management Module 10: Ecommerce Analytics Course 02: Strategic Marketing & Planning Module 1: An Introduction to Strategic Planning Module 2: Development of a Strategic Plan Module 3: Strategic Planning for Marketing Module 4: Strategic and Marketing Analysis Module 5: Internal Analysis Module 6: External Analysis Module 7: Market Segmentation, Targeting and Positioning Module 8: Approaches to Customer Analysis Module 9: Approaches to Competitor Analysis Course 03: Social Media Marketing Strategy The Rise Of Social Media Conducting Market Analysis Auditing Social Media Setting Goals And Selecting Platforms Creating The Social Media Policy Integrating Marketing Strategies Developing Effective Content Understanding The Popular Platforms Launching Successful Campaigns Managing The Community Providing Customer Service Measuring, Analyzing And Reporting The Social Media Strategist Career =========>>>>> And 8 More Courses <<<<<========= How will I get my Certificate? After successfully completing the course, you will be able to order your QLS Endorsed Certificates and CPD Accredited Certificates as proof of your achievement. PDF Certificate: Free (Previously it was £12.99*11 = £143) QLS Endorsed Hard Copy Certificate: Free (For The Title Course: Previously it was £119) CPD 260 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Anyone interested in learning more about the topic is advised to take this bundle. This bundle is ideal for: Requirements You will not need any prior background or expertise to enrol in this bundle. Career path After completing this bundle, you are to start your career or begin the next phase of your career. E-commerce Manager Marketing Guru Social Media Whiz SEO Mastermind Sales Champion Certificates CPD Accredited Digital Certificate Digital certificate - Included Upon passing the Course, you need to order a Digital Certificate for each of the courses inside this bundle as proof of your new skills that are accredited by CPD QS for Free. Diploma in E-Commerce Management at QLS Level 5 Hard copy certificate - Included Please note that International students have to pay an additional £10 as a shipment fee.

Embark on a captivating journey into the world of artificial intelligence with our course, 'Machine Learning Basics.' This voyage begins with an immersive introduction, setting the stage for an exploration into the intricate and fascinating realm of machine learning. Envision yourself unlocking the mysteries of algorithms and data patterns, essential skills in today's technology-driven landscape. The course offers a comprehensive foray into the core principles of machine learning, starting from the very basics and gradually building to more complex concepts, making it an ideal path for beginners and enthusiasts alike. As you delve deeper, each section unravels a vital component of machine learning. Grasp the essentials of regression analysis, understand the role of predictors, and navigate through the functionalities of Minitab, a key tool in data analysis. Journey through the structured world of regression trees and binary logistic regression, and master the art of classification trees. The course also emphasizes the importance of data cleaning and constructing robust data models, culminating in the achievement of learning success. This course is not just an educational experience; it's a gateway to the future of data science and AI. Learning Outcomes Comprehend the basic principles and applications of machine learning. Develop proficiency in regression analysis and predictor identification. Gain practical skills in Minitab for data analysis. Understand and apply regression and classification trees. Acquire expertise in data cleaning and model creation. Why choose this Machine Learning Basics course? Unlimited access to the course for a lifetime. Opportunity to earn a certificate accredited by the CPD Quality Standards and CIQ after completing this course. Structured lesson planning in line with industry standards. Immerse yourself in innovative and captivating course materials and activities. Assessments designed to evaluate advanced cognitive abilities and skill proficiency. Flexibility to complete the Course at your own pace, on your own schedule. Receive full tutor support throughout the week, from Monday to Friday, to enhance your learning experience. Unlock career resources for CV improvement, interview readiness, and job success. Who is this Machine Learning Basics course for? Novices eager to delve into machine learning. Data enthusiasts looking to enhance their analytical skills. Professionals in IT and related fields expanding their expertise. Academics and students in computer science and data studies. Career changers interested in the field of data science and AI. Career path Data Analyst - £30,000 to £55,000 Machine Learning Engineer - £40,000 to £80,000 AI Developer - £35,000 to £75,000 Business Intelligence Analyst - £32,000 to £60,000 Research Scientist (Machine Learning) - £45,000 to £85,000 Software Engineer (AI Specialization) - £38,000 to £70,000 Prerequisites This Machine Learning Basics does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Machine Learning Basics was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection. Certification After studying the course materials, there will be a written assignment test which you can take at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £4.99 Original Hard Copy certificates need to be ordered at an additional cost of £8. Course Curriculum Section 01: Introduction Introduction to Supervised Machine Learning 00:06:00 Section 02: Regression Introduction to Regression 00:13:00 Evaluating Regression Models 00:11:00 Conditions for Using Regression Models in ML versus in Classical Statistics 00:21:00 Statistically Significant Predictors 00:09:00 Regression Models Including Categorical Predictors. Additive Effects 00:20:00 Regression Models Including Categorical Predictors. Interaction Effects 00:18:00 Section 03: Predictors Multicollinearity among Predictors and its Consequences 00:21:00 Prediction for New Observation. Confidence Interval and Prediction Interval 00:06:00 Model Building. What if the Regression Equation Contains 'Wrong' Predictors? 00:13:00 Section 04: Minitab Stepwise Regression and its Use for Finding the Optimal Model in Minitab 00:13:00 Regression with Minitab. Example. Auto-mpg: Part 1 00:17:00 Regression with Minitab. Example. Auto-mpg: Part 2 00:18:00 Section 05: Regression Trees The Basic idea of Regression Trees 00:18:00 Regression Trees with Minitab. Example. Bike Sharing: Part1 00:15:00 Regression Trees with Minitab. Example. Bike Sharing: Part 2 00:10:00 Section 06: Binary Logistics Regression Introduction to Binary Logistics Regression 00:23:00 Evaluating Binary Classification Models. Goodness of Fit Metrics. ROC Curve. AUC 00:20:00 Binary Logistic Regression with Minitab. Example. Heart Failure: Part 1 00:16:00 Binary Logistic Regression with Minitab. Example. Heart Failure: Part 2 00:18:00 Section 07: Classification Trees Introduction to Classification Trees 00:12:00 Node Splitting Methods 1. Splitting by Misclassification Rate 00:20:00 Node Splitting Methods 2. Splitting by Gini Impurity or Entropy 00:11:00 Predicted Class for a Node 00:06:00 The Goodness of the Model - 1. Model Misclassification Cost 00:11:00 The Goodness of the Model - 2 ROC. Gain. Lit Binary Classification 00:15:00 The Goodness of the Model - 3. ROC. Gain. Lit. Multinomial Classification 00:08:00 Predefined Prior Probabilities and Input Misclassification Costs 00:11:00 Building the Tree 00:08:00 Classification Trees with Minitab. Example. Maintenance of Machines: Part 1 00:17:00 Classification Trees with Miitab. Example. Maintenance of Machines: Part 2 00:10:00 Section 08: Data Cleaning Data Cleaning: Part 1 00:16:00 Data Cleaning: Part 2 00:17:00 Creating New Features 00:12:00 Section 09: Data Models Polynomial Regression Models for Quantitative Predictor Variables 00:20:00 Interactions Regression Models for Quantitative Predictor Variables 00:15:00 Qualitative and Quantitative Predictors: Interaction Models 00:28:00 Final Models for Duration and TotalCharge: Without Validation 00:18:00 Underfitting or Overfitting: The 'Just Right Model' 00:18:00 The 'Just Right' Model for Duration 00:16:00 The 'Just Right' Model for Duration: A More Detailed Error Analysis 00:12:00 The 'Just Right' Model for TotalCharge 00:14:00 The 'Just Right' Model for ToralCharge: A More Detailed Error Analysis 00:06:00 Section 10: Learning Success Regression Trees for Duration and TotalCharge 00:18:00 Predicting Learning Success: The Problem Statement 00:07:00 Predicting Learning Success: Binary Logistic Regression Models 00:17:00 Predicting Learning Success: Classification Tree Models 00:09:00

HGV Training (Heavy Goods Vehicle) Training Get Hard Copy + PDF Certificates + Transcript + Student ID Card as a Gift - Enrol HGV Training Now Do you want to learn what it takes to be an HGV Driver? With approximately 100k vacancies UK-wide and earning potential of up to £60k a year, there has never been a better time to be an HGV driver in the UK. Our HGV Training bundle will help you learn the essential parts of the Large Goods Vehicle (LGV), transport management, manual handling, import/export, logistics management, vehicle repair and much more to become a well-versed HGV driver. This HGV Training Bundle Consists of the following Premium courses: Course 01: Heavy Goods Vehicle (HGV Training) Course 02: Delivery Driver Training Course 03: Transport Management Diploma Course 04: Freight Consultant Training Course 05: Logistic Management Course 06: Import/Export Processing Course 07: Car Mechanic and Repair Training Course 08: MET Technician Course 09: Driver Safety Awareness Certificate - CPD Certified Course 10: Engine Lubricant System Training - Level 4 Course 11: Emergency First Aid and Incident Management at Work Enrol now in HGV Training to advance your career, and use the premium study materials from Apex Learning. Benefits you'll get from choosing Apex Learning for this HGV Training: Pay once and get lifetime access to 14 CPD courses in this HGV Training Course Free e-Learning App for engaging reading materials & helpful assistance Certificates, student ID for the HGV Training course included in a one-time fee Free up your time - don't waste time and money travelling for classes Accessible, informative modules of HGV Training designed by expert instructors Learn about HGV Training at your ease - anytime, from anywhere Study the HGV Training from your computer, tablet or mobile device CPD accredited HGV Training course - improve the chance of gaining professional skills So enrol now in this HGV Training Bundle to advance your career! ***HGV Training*** The curriculum of HGV Training Bundle Course 01: Heavy Goods Vehicle (HGV Training) Module 01: Knowing Your LGV Module 02: Characteristics of Vehicle Module 03: Vehicle Limit Module 04: Loads and Load Restraint Module 05: Drivers' Hours and Records Module 06: Vehicles and Driving Module 07: Health and Conduct Module 08: Your LGV Module 09: Qualified LGV Driver Module 10: Provisional LGV Licence Module 11: CPC Test Part 01 and 02 Module 12: CPC Test Part 03 and 04 Module 13: After Getting Qualification =========>>>>> And 10 More Courses <<<<<========= How will I get my HGV Training Certificate? After successfully completing the HGV Training course, you will be able to order your CPD Accredited Certificates (PDF + Hard Copy) as proof of your achievement. PDF Certificate: Free (For The Title Course) Hard Copy Certificate: Free (For The Title Course) So enrol now in this HGV Training Bundle to advance your career! CPD 110 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Anyone from any background can enrol in this HGV Training bundle. Persons with similar professions can also refresh or strengthen their skills by enrolling in this HGV Training course. Students can take this course to gather professional knowledge besides their study or for the future. Requirements Our HGV Training is fully compatible with PC's, Mac's, laptops, tablets and Smartphone devices. This HGV Training course has been designed to be fully compatible with tablets and smartphones, so you can access your course on Wi-Fi, 3G or 4G. There is no time limit for completing this HGV Training; it can be studied in your own time at your own pace. Career path HGV Training (Heavy Goods Vehicle) HGV Driver - £22,131 - £58,500 annually HGV Fitter - £20,431 - £38,131 annually HGV Technician - £28,131- £48,000 annually Certificates Certificate of completion Digital certificate - Included You will get the PDF Certificate for the title course (Transport Management Diploma) absolutely Free! Certificate of completion Hard copy certificate - Included You will get the Hard Copy certificate for the title course (Transport Management Diploma) absolutely Free! Other Hard Copy certificates are available for £10 each. Please Note: The delivery charge inside the UK is £3.99, and the international students must pay a £9.99 shipping cost.

Looking to bring clarity to chaos? This Operations Management course is your go-to resource for mastering the art of running things smoothly. Designed with precision, it focuses on streamlining processes, improving efficiency, and sharpening decision-making across various business functions. Whether you're overseeing supply chains, production lines, or internal workflows, this course offers a structured approach to getting things done right—and on time. As part of a CPDQS Accredited Bundle, it brings credibility and weight to your professional development without adding extra fluff. It’s all about understanding how operations tick and making them tick better. With carefully crafted modules, it guides you through essential concepts in planning, control, quality, and strategy—without the waffle. Whether you're stepping into a new role or levelling up your current one, this course is tailored to those who prefer substance over slogans. No-nonsense, straight-talking, and entirely online—just how good learning should be. Key Features of Operations Management Bundle CPD Accredited Operations Management Course Instant PDF certificate Fully online, interactive Operations Managementcourse Self-paced learning and laptop, tablet, smartphone-friendly 24/7 Learning Assistance Discounts on bulk purchases Enrol now in this Operations Management Bundle course to excel! To become successful in your profession, you must have a specific set of Operations Management skills to succeed in today's competitive world. In this in-depth Operations Managementtraining course, you will develop the most in-demand Operations Management skills to kickstart your career, as well as upgrade your existing knowledge & skills. Operations Management Curriculum Course 01: Operations Management Course 02: Project Planning and Execution Course 03: Budget & Forecast Course 04: Strategic Planning and Implementation Skills Course 05: Project Management Course 06: Facilities & Maintenance Operative Course 07: Six Sigma Course 08: Stakeholder Management Course 09: Procurement and Supply Chain Management Course 10: Leadership and People Management Diploma Course 11: Financial Reporting Course 12: Line Management Course 13: Logistics Management Course 14: Risk Management Course 15: Change Management Course 16: Time Management in The Workplace Course 17: Administrative Assistant and Organizational Skills Course 18: Compliance and Risk Management Course 19: Communication Skills Course 20: Finance for Non finance Managers Accreditation This Operations Management bundle courses are CPD accredited, providing you with up-to-date skills and knowledge and helping you to become more competent and effective in your chosen field. Certification Once you've successfully completed your Operations Management course, you will immediately be sent a digital certificate. Also, you can have your printed certificate delivered by post (shipping cost £3.99). CPD 200 CPD hours / points Accredited by CPD Quality Standards Who is this course for? This course is ideal for all employees or anyone who genuinely wishes to learn more about Operations Management basics. Requirements No prior degree or experience is required to enrol in this course. Career path This Operations Management Course will help you to explore avariety of career paths in the related industry. Certificates Digital certificate Digital certificate - Included Hardcopy Certificate Hard copy certificate - Included Hardcopy Certificate (UK Delivery): For those who wish to have a physical token of their achievement, we offer a high-quality, printed certificate. This hardcopy certificate is also provided free of charge. However, please note that delivery fees apply. If your shipping address is within the United Kingdom, the delivery fee will be only £3.99. Hardcopy Certificate (International Delivery): For all international addresses outside of the United Kingdom, the delivery fee for a hardcopy certificate will be only £10.

Getting Started The main aim of the OTHM Level 7 Diploma in Data Science is to enhance the knowledge and skills required to extract business-oriented insights from data. This involves comprehending how value and information circulate in a business and utilising this knowledge to recognise potential business prospects.The main aim of the OTHM Level 7 Diploma in Data Science is to enhance the knowledge and skills required to extract business-oriented insights from data. This involves comprehending how value and information circulate in a business and utilising this knowledge to recognise potential business prospects. Key Benefits This qualification will bring you many vital benefits, such as; Learners can gain the essential subject knowledge needed to progress successfully into further study or the world of work. Refreshed content that is closely aligned with employer and higher education needs Develop a comprehensive knowledge of classical data analytics, including statistical inference, predictive modelling, time series analysis and data reduction. Become familiar with and use the tools and techniques used in data visualisation. Assessments that consider cognitive skills along with affective and applied skills Key Highlights Do you wish to be a Data Scientist? Then, The OTHM Level 7 Diploma in Data Science program offered by the School of Business and Technology London is the right solution for you. Remember! The assessment for the qualification is done based on assignments only, and you do not need to worry about writing any exam. With the School of Business and Technology London, you can complete the qualification at your own pace, choosing online or blended learning from the comfort of your home. Learning and pathway materials and study guides developed by our OTHM-approved tutors will be available around the clock in our cutting-edge learning management system. Most importantly, at the School of Business and Technology London, we will provide comprehensive tutor support through our dedicated support desk. If you choose your course with blended learning, you will also enjoy live sessions with an assigned tutor, which you can book at your convenience. Career Pathways The OTHM Level 7 Diploma in Data Science can open many career pathways including, but not limited to: Data scientist- Est. Salary £59,680 Data Analyst- Est. Salary £42,984 Business Analyst-Est. Salary £54,413   About Awarding Body OTHM is an established and recognised Awarding Organisation (Certification Body) launched in 2003. OTHM has already made a mark in the UK and global online education scenario by creating and maintaining a user-friendly and skill based learning environment. OTHM has both local and international recognition which aids OTHM graduates to enhance their employability skills as well as allowing them to join degree and/or Master top-up programmes. OTHM qualifications has assembled a reputation for maintaining significant skills in a wide range of job roles and industries which comprises Business Studies, Leadership, Tourism and Hospitality Management, Health and Social Care, Information Technology, Accounting and Finance, Logistics and Supply Chain Management. Learners must request before enrolment to interchange unit(s) other than the preselected units shown in the SBTL website because we need to make sure the availability of learning materials for the requested unit(s). SBTL will reject an application if the learning materials for the requested interchange unit(s) are unavailable. Learners are not allowed to make any request to interchange unit(s) once enrolment is complete. UNIT1- Data Science Foundations Reference No : Unit 1 - F/650/5562 Credit : 20 || TQT : 200 Hours This unit introduces various data science concepts, including data administration, governance, and big data sources. UNIT2- Probability and Statistics for Data Analysis Reference No : Unit 2 - H/650/5563 Credit : 20 || TQT : 200 Hours The objective of this unit is to offer a comprehensive introduction to the fundamental principles of probability and statistics, starting from the basics. It will cover a wide spectrum of data analysis procedures and methodologies. UNIT3- Advanced Predictive Modeling Reference No : Unit 3 - J/650/5564 Credit : 20 || TQT : 200 Hours You will become acquainted with key predictive modelling methods and their underlying foundational principles in this unit. UNIT4- Data Analysis and Visualisation Reference No : Unit 4 - K/650/5565 Credit : 20 || TQT : 200 Hours This unit serves as a crucial foundation for grasping the core concepts of the data analysis process, encompassing data collection, data cleansing, data analysis, and the effective communication of insights through visualisations and dashboard tools. UNIT5- Data Mining Machine Learning and Artificial Intelligence Reference No : Unit 5 - J/650/5573 Credit : 20 || TQT : 200 Hours The primary aim of this unit is to provide an introduction to the scientific principles underpinning machine intelligence and to explore the philosophical discourse surrounding the endeavour to simulate human intelligence for addressing real-world challenges. UNIT6- Advanced Computing Research Methods Reference No : Unit 6 - L/650/5566 Credit : 20 || TQT : 200 Hours This unit aims to enhance learners' skills in preparing for diverse forms of academic computing research by guiding them through creating and designing a research proposal. Delivery Methods School of Business & Technology London provides various flexible delivery methods to its learners, including online learning and blended learning. Thus, learners can choose the mode of study as per their choice and convenience. The program is self-paced and accomplished through our cutting-edge Learning Management System. Learners can interact with tutors by messaging through the SBTL Support Desk Portal System to discuss the course materials, get guidance and assistance and request assessment feedbacks on assignments. We at SBTL offer outstanding support and infrastructure for both online and blended learning. We indeed pursue an innovative learning approach where traditional regular classroom-based learning is replaced by web-based learning and incredibly high support level. Learners enrolled at SBTL are allocated a dedicated tutor, whether online or blended learning, who provide learners with comprehensive guidance and support from start to finish. The significant difference between blended learning and online learning methods at SBTL is the Block Delivery of Online Live Sessions. Learners enrolled at SBTL on blended learning are offered a block delivery of online live sessions, which can be booked in advance on their convenience at additional cost. These live sessions are relevant to the learners' program of study and aim to enhance the student's comprehension of research, methodology and other essential study skills. We try to make these live sessions as communicating as possible by providing interactive activities and presentations. Resources and Support School of Business & Technology London is dedicated to offering excellent support on every step of your learning journey. School of Business & Technology London occupies a centralised tutor support desk portal. Our support team liaises with both tutors and learners to provide guidance, assessment feedback, and any other study support adequately and promptly. Once a learner raises a support request through the support desk portal (Be it for guidance, assessment feedback or any additional assistance), one of the support team members assign the relevant to request to an allocated tutor. As soon as the support receives a response from the allocated tutor, it will be made available to the learner in the portal. The support desk system is in place to assist the learners adequately and streamline all the support processes efficiently. Quality learning materials made by industry experts is a significant competitive edge of the School of Business & Technology London. Quality learning materials comprised of structured lecture notes, study guides, practical applications which includes real-world examples, and case studies that will enable you to apply your knowledge. Learning materials are provided in one of the three formats, such as PDF, PowerPoint, or Interactive Text Content on the learning portal. How does the Online Learning work at SBTL? We at SBTL follow a unique approach which differentiates us from other institutions. Indeed, we have taken distance education to a new phase where the support level is incredibly high.Now a days, convenience, flexibility and user-friendliness outweigh demands. Today, the transition from traditional classroom-based learning to online platforms is a significant result of these specifications. In this context, a crucial role played by online learning by leveraging the opportunities for convenience and easier access. It benefits the people who want to enhance their career, life and education in parallel streams. SBTL's simplified online learning facilitates an individual to progress towards the accomplishment of higher career growth without stress and dilemmas. How will you study online? With the School of Business & Technology London, you can study wherever you are. You finish your program with the utmost flexibility. You will be provided with comprehensive tutor support online through SBTL Support Desk portal. How will I get tutor support online? School of Business & Technology London occupies a centralised tutor support desk portal, through which our support team liaise with both tutors and learners to provide guidance, assessment feedback, and any other study support adequately and promptly. Once a learner raises a support request through the support desk portal (Be it for guidance, assessment feedback or any additional assistance), one of the support team members assign the relevant to request to an allocated tutor. As soon as the support receive a response from the allocated tutor, it will be made available to the learner in the portal. The support desk system is in place to assist the learners adequately and to streamline all the support process efficiently. Learners should expect to receive a response on queries like guidance and assistance within 1 - 2 working days. However, if the support request is for assessment feedback, learners will receive the reply with feedback as per the time frame outlined in the Assessment Feedback Policy.

Getting Started The OTHM Level 7 Diploma in Immersive Software Engineering aims to equip learners with advanced-level knowledge and skills to design, develop, and evaluate immersive software engineering systems. By completing this qualification, learners will acquire the skills to support research and innovation in various domains, such as Web and cloud technologies, Security, Automation, Data analytics, and Project methodologies. The primary objective of this diploma is to develop critical thinking and research skills in learners to identify and address complex problems in the software engineering field. Key Benefits This qualification will bring you many vital benefits, such as; The study program is designed to be both stimulating and challenging, providing learners with a chance to gain essential subject knowledge to help them succeed in further studies or the workforce. The program's content has been updated to match the latest employer and higher education requirements. Assessments evaluate both cognitive and affective skills, along with applied skills. Learners will develop valuable knowledge and academic skills, including active research, effective writing and analysis, creative problem-solving, decision-making, and digital literacy. Key Highlights Are you aspiring to become a Software Developer? Then, the OTHM Level 7 Diploma in Immersive Software Engineering program offered by the School of Business and Technology London is the right solution for you. Remember! The assessment for the qualification is done based on assignments only, and you do not need to worry about writing any exam. With the School of Business and Technology London, you can complete the qualification at your own pace, choosing online or blended learning from the comfort of your home. Learning and pathway materials and study guides developed by our OTHM-approved tutors will be available around the clock in our cutting-edge learning management system. Most importantly, at the School of Business and Technology London, we will provide comprehensive tutor support through our dedicated support desk. If you choose your course with blended learning, you will also enjoy live sessions with an assigned tutor, which you can book at your convenience. Career Pathways The OTHM Level 7 Diploma in Immersive Software Engineering can open many career pathways including, but not limited to: Chief technology officer; Est. Salary £1,41,489 per annum Senior software engineer; Est. Salary £55,913 per annum Junior software engineer; Est. Salary £25,904 per annum Team Leader; Est. salary £27,903 per annum     About Awarding Body OTHM is an established and recognised Awarding Organisation (Certification Body) launched in 2003. OTHM has already made a mark in the UK and global online education scenario by creating and maintaining a user-friendly and skill based learning environment. OTHM has both local and international recognition which aids OTHM graduates to enhance their employability skills as well as allowing them to join degree and/or Master top-up programmes. OTHM qualifications has assembled a reputation for maintaining significant skills in a wide range of job roles and industries which comprises Business Studies, Leadership, Tourism and Hospitality Management, Health and Social Care, Information Technology, Accounting and Finance, Logistics and Supply Chain Management. Learners must request before enrolment to interchange unit(s) other than the preselected units shown in the SBTL website because we need to make sure the availability of learning materials for the requested unit(s). SBTL will reject an application if the learning materials for the requested interchange unit(s) are unavailable. Learners are not allowed to make any request to interchange unit(s) once enrolment is complete. UNIT1- Security Engineering Reference No : Unit 1 - F/650/7994 Credit : 20 || TQT : 200 Hours This unit teaches secure software development, system hardening, authentication, encryption, network security, and web application architecture. UNIT2- Software Programming Principles and Practices in Java I Reference No : Unit 2 - H/650/7995 Credit : 20 || TQT : 200 Hours This unit teaches learners about programming languages, including what it is, how it works, and how to interact with computers. Learners will learn the basics through real-world coding examples and regular coding assignments. UNIT3- Agile Project Management Reference No : Unit 3 - J/650/7996 Credit : 20 || TQT : 200 Hours This unit covers project management, Scrum, and Kanab for IT product development. Build products iteratively and optimize value flow for customers. UNIT4- Cloud Computing & DevOps Reference No : Unit 4 - K/650/7997 Credit : 20 || TQT : 200 Hours This unit teaches cloud computing, DevOps, and various cloud models (IaaS, PaaS, SaaS), including different cloud services. UNIT5- Database & SQL Programming Reference No : Unit 5 - L/650/7998 Credit : 20 || TQT : 200 Hours The unit teaches learners the limitations of traditional storage systems, how modern relational databases overcome these challenges, and programming skills to communicate with databases using SQL. UNIT6- Web Designing Reference No : Unit 6 - M/650/7999 Credit : 20 || TQT : 200 Hours This course teaches learners to create HTML, CSS, and JavaScript web pages. Design sites, use styles, tables, lists, and HTML user input properties, and learn JavaScript basics. Delivery Methods School of Business & Technology London provides various flexible delivery methods to its learners, including online learning and blended learning. Thus, learners can choose the mode of study as per their choice and convenience. The program is self-paced and accomplished through our cutting-edge Learning Management System. Learners can interact with tutors by messaging through the SBTL Support Desk Portal System to discuss the course materials, get guidance and assistance and request assessment feedbacks on assignments. We at SBTL offer outstanding support and infrastructure for both online and blended learning. We indeed pursue an innovative learning approach where traditional regular classroom-based learning is replaced by web-based learning and incredibly high support level. Learners enrolled at SBTL are allocated a dedicated tutor, whether online or blended learning, who provide learners with comprehensive guidance and support from start to finish. The significant difference between blended learning and online learning methods at SBTL is the Block Delivery of Online Live Sessions. Learners enrolled at SBTL on blended learning are offered a block delivery of online live sessions, which can be booked in advance on their convenience at additional cost. These live sessions are relevant to the learners' program of study and aim to enhance the student's comprehension of research, methodology and other essential study skills. We try to make these live sessions as communicating as possible by providing interactive activities and presentations. Resources and Support School of Business & Technology London is dedicated to offering excellent support on every step of your learning journey. School of Business & Technology London occupies a centralised tutor support desk portal. Our support team liaises with both tutors and learners to provide guidance, assessment feedback, and any other study support adequately and promptly. Once a learner raises a support request through the support desk portal (Be it for guidance, assessment feedback or any additional assistance), one of the support team members assign the relevant to request to an allocated tutor. As soon as the support receives a response from the allocated tutor, it will be made available to the learner in the portal. The support desk system is in place to assist the learners adequately and streamline all the support processes efficiently. Quality learning materials made by industry experts is a significant competitive edge of the School of Business & Technology London. Quality learning materials comprised of structured lecture notes, study guides, practical applications which includes real-world examples, and case studies that will enable you to apply your knowledge. Learning materials are provided in one of the three formats, such as PDF, PowerPoint, or Interactive Text Content on the learning portal. How does the Online Learning work at SBTL? We at SBTL follow a unique approach which differentiates us from other institutions. Indeed, we have taken distance education to a new phase where the support level is incredibly high.Now a days, convenience, flexibility and user-friendliness outweigh demands. Today, the transition from traditional classroom-based learning to online platforms is a significant result of these specifications. In this context, a crucial role played by online learning by leveraging the opportunities for convenience and easier access. It benefits the people who want to enhance their career, life and education in parallel streams. SBTL's simplified online learning facilitates an individual to progress towards the accomplishment of higher career growth without stress and dilemmas. How will you study online? With the School of Business & Technology London, you can study wherever you are. You finish your program with the utmost flexibility. You will be provided with comprehensive tutor support online through SBTL Support Desk portal. How will I get tutor support online? School of Business & Technology London occupies a centralised tutor support desk portal, through which our support team liaise with both tutors and learners to provide guidance, assessment feedback, and any other study support adequately and promptly. Once a learner raises a support request through the support desk portal (Be it for guidance, assessment feedback or any additional assistance), one of the support team members assign the relevant to request to an allocated tutor. As soon as the support receive a response from the allocated tutor, it will be made available to the learner in the portal. The support desk system is in place to assist the learners adequately and to streamline all the support process efficiently. Learners should expect to receive a response on queries like guidance and assistance within 1 - 2 working days. However, if the support request is for assessment feedback, learners will receive the reply with feedback as per the time frame outlined in the Assessment Feedback Policy.

Duration 2 Days 12 CPD hours This course is intended for Audience: Data Scientists, Software Developers, IT Architects, and Technical Managers. Participants should have the general knowledge of statistics and programming Also familiar with Python Overview ? NumPy, pandas, Matplotlib, scikit-learn ? Python REPLs ? Jupyter Notebooks ? Data analytics life-cycle phases ? Data repairing and normalizing ? Data aggregation and grouping ? Data visualization ? Data science algorithms for supervised and unsupervised machine learning Covers theoretical and technical aspects of using Python in Applied Data Science projects and Data Logistics use cases. Python for Data Science ? Using Modules ? Listing Methods in a Module ? Creating Your Own Modules ? List Comprehension ? Dictionary Comprehension ? String Comprehension ? Python 2 vs Python 3 ? Sets (Python 3+) ? Python Idioms ? Python Data Science ?Ecosystem? ? NumPy ? NumPy Arrays ? NumPy Idioms ? pandas ? Data Wrangling with pandas' DataFrame ? SciPy ? Scikit-learn ? SciPy or scikit-learn? ? Matplotlib ? Python vs R ? Python on Apache Spark ? Python Dev Tools and REPLs ? Anaconda ? IPython ? Visual Studio Code ? Jupyter ? Jupyter Basic Commands ? Summary Applied Data Science ? What is Data Science? ? Data Science Ecosystem ? Data Mining vs. Data Science ? Business Analytics vs. Data Science ? Data Science, Machine Learning, AI? ? Who is a Data Scientist? ? Data Science Skill Sets Venn Diagram ? Data Scientists at Work ? Examples of Data Science Projects ? An Example of a Data Product ? Applied Data Science at Google ? Data Science Gotchas ? Summary Data Analytics Life-cycle Phases ? Big Data Analytics Pipeline ? Data Discovery Phase ? Data Harvesting Phase ? Data Priming Phase ? Data Logistics and Data Governance ? Exploratory Data Analysis ? Model Planning Phase ? Model Building Phase ? Communicating the Results ? Production Roll-out ? Summary Repairing and Normalizing Data ? Repairing and Normalizing Data ? Dealing with the Missing Data ? Sample Data Set ? Getting Info on Null Data ? Dropping a Column ? Interpolating Missing Data in pandas ? Replacing the Missing Values with the Mean Value ? Scaling (Normalizing) the Data ? Data Preprocessing with scikit-learn ? Scaling with the scale() Function ? The MinMaxScaler Object ? Summary Descriptive Statistics Computing Features in Python ? Descriptive Statistics ? Non-uniformity of a Probability Distribution ? Using NumPy for Calculating Descriptive Statistics Measures ? Finding Min and Max in NumPy ? Using pandas for Calculating Descriptive Statistics Measures ? Correlation ? Regression and Correlation ? Covariance ? Getting Pairwise Correlation and Covariance Measures ? Finding Min and Max in pandas DataFrame ? Summary Data Aggregation and Grouping ? Data Aggregation and Grouping ? Sample Data Set ? The pandas.core.groupby.SeriesGroupBy Object ? Grouping by Two or More Columns ? Emulating the SQL's WHERE Clause ? The Pivot Tables ? Cross-Tabulation ? Summary Data Visualization with matplotlib ? Data Visualization ? What is matplotlib? ? Getting Started with matplotlib ? The Plotting Window ? The Figure Options ? The matplotlib.pyplot.plot() Function ? The matplotlib.pyplot.bar() Function ? The matplotlib.pyplot.pie () Function ? Subplots ? Using the matplotlib.gridspec.GridSpec Object ? The matplotlib.pyplot.subplot() Function ? Hands-on Exercise ? Figures ? Saving Figures to File ? Visualization with pandas ? Working with matplotlib in Jupyter Notebooks ? Summary Data Science and ML Algorithms in scikit-learn ? Data Science, Machine Learning, AI? ? Types of Machine Learning ? Terminology: Features and Observations ? Continuous and Categorical Features (Variables) ? Terminology: Axis ? The scikit-learn Package ? scikit-learn Estimators ? Models, Estimators, and Predictors ? Common Distance Metrics ? The Euclidean Metric ? The LIBSVM format ? Scaling of the Features ? The Curse of Dimensionality ? Supervised vs Unsupervised Machine Learning ? Supervised Machine Learning Algorithms ? Unsupervised Machine Learning Algorithms ? Choose the Right Algorithm ? Life-cycles of Machine Learning Development ? Data Split for Training and Test Data Sets ? Data Splitting in scikit-learn ? Hands-on Exercise ? Classification Examples ? Classifying with k-Nearest Neighbors (SL) ? k-Nearest Neighbors Algorithm ? k-Nearest Neighbors Algorithm ? The Error Rate ? Hands-on Exercise ? Dimensionality Reduction ? The Advantages of Dimensionality Reduction ? Principal component analysis (PCA) ? Hands-on Exercise ? Data Blending ? Decision Trees (SL) ? Decision Tree Terminology ? Decision Tree Classification in Context of Information Theory ? Information Entropy Defined ? The Shannon Entropy Formula ? The Simplified Decision Tree Algorithm ? Using Decision Trees ? Random Forests ? SVM ? Naive Bayes Classifier (SL) ? Naive Bayesian Probabilistic Model in a Nutshell ? Bayes Formula ? Classification of Documents with Naive Bayes ? Unsupervised Learning Type: Clustering ? Clustering Examples ? k-Means Clustering (UL) ? k-Means Clustering in a Nutshell ? k-Means Characteristics ? Regression Analysis ? Simple Linear Regression Model ? Linear vs Non-Linear Regression ? Linear Regression Illustration ? Major Underlying Assumptions for Regression Analysis ? Least-Squares Method (LSM) ? Locally Weighted Linear Regression ? Regression Models in Excel ? Multiple Regression Analysis ? Logistic Regression ? Regression vs Classification ? Time-Series Analysis ? Decomposing Time-Series ? Summary Lab Exercises Lab 1 - Learning the Lab Environment Lab 2 - Using Jupyter Notebook Lab 3 - Repairing and Normalizing Data Lab 4 - Computing Descriptive Statistics Lab 5 - Data Grouping and Aggregation Lab 6 - Data Visualization with matplotlib Lab 7 - Data Splitting Lab 8 - k-Nearest Neighbors Algorithm Lab 9 - The k-means Algorithm Lab 10 - The Random Forest Algorithm